Syllabus
   Lecture 01      Describing Inverse Problems
   Lecture 02      Probability and Measurement Error, Part 1
   Lecture 03      Probability and Measurement Error, Part 2 
   Lecture 04      The L  Norm and Simple Least Squares
                        2
   Lecture 05      A Priori Information and Weighted Least Squared
   Lecture 06      Resolution and Generalized Inverses
   Lecture 07      Backus-Gilbert Inverse and the Trade Off of Resolution and Variance
   Lecture 08      The Principle of Maximum Likelihood
   Lecture 09      Inexact Theories
   Lecture 10      Nonuniqueness and Localized Averages
   Lecture 11      Vector Spaces and Singular Value Decomposition
   Lecture 12      Equality and Inequality Constraints
   Lecture 13      L , L  Norm Problems and Linear Programming
                    1   ∞
   Lecture 14      Nonlinear Problems: Grid and Monte Carlo Searches 
   Lecture 15      Nonlinear Problems: Newton’s Method 
   Lecture 16      Nonlinear Problems:  Simulated Annealing and Bootstrap Confidence Intervals 
   Lecture 17      Factor Analysis
   Lecture 18      Varimax Factors, Empircal Orthogonal Functions
   Lecture 19      Backus-Gilbert Theory for Continuous Problems; Radon’s Problem
   Lecture 20      Linear Operators and Their Adjoints
   Lecture 21      Fréchet Derivatives
   Lecture 22      Exemplary Inverse Problems, incl. Filter Design
   Lecture 23      Exemplary Inverse Problems, incl. Earthquake Location
   Lecture 24      Exemplary Inverse Problems, incl. Vibrational Problems
    Purpose of the Lecture
    Introduce Newton’s Method
   Generalize it to an Implicit Theory
   Introduce the Gradient Method
        Part 1
     Newton’s Method
       grid search
     Monte Carlo Method
    are completely undirected
       alternative
    take directions from the
      local properties
   of the error function E(m)
            Newton’s Method
                             (p)
             start with a guess m
       (p) 
 near m  , approximate E(m) as a parabola and 
              find its minimum
      set new guess to this value and iterate